The goal of this program is development of signal processing methods that will expand the role MEG/EEG functional brain imaging as a clinical tool for diagnosis of brain dysfunction and as a scientific tool for the study of brain development and function. The research program introduces a new approach in which both the measured data and underlying cortical surface are represented using multiresolution basis function expansions. Improved performance is obtained by developing signal processing, source localization, and imaging algorithms that exploit the basis function expansion. The specific aims of the proposed studies are: 1) To develop basis function expansions that jointly represent the spatio-temporal distribution of brain activity at the sensors and on the cortical surface. Our proposed multiresolution approach employs a parsimonious representation for brain activity at different temporal and spatial scales, a critical property for effective solution of various aspects of the inverse problem. 2) To develop robust signal processing algorithms that exploit the basis function representation to perform detection, localization and monitoring of multiple sources, and imaging of the activity on the cortical surface. The proposed algorithms will have reduced complexity and improved performance relative to existing methods. 3) To characterize the performance of the algorithms developed under Aims 1 and 2 using nonparametric statistical analysis and computer simulation. 4) To obtain human subject pilot data demonstrating the effectiveness of the algorithms developed under Aims 1 and 2. [unreadable] [unreadable] [unreadable]